A motor control system and methodology require that the position of the motor (e.g., positions of the rotor angles) be determined, known, derived, and/or estimated. One way of determining motor position is by using a sensor as part of the motor control system. However, a sensor adds to the costs, hardware, and space consumption of the overall motor control system,
Another way of determining motor position is by using a sensorless motor control approach. The sensorless motor control approach does not use a sensor to sense the position of the motor but instead typically uses an observer. The observer is herein defined as an operational block, device, or system that determines the motor position as a function of the electrical input/output (“I/O”) of the motor. They have been developed to avoid at least some of the issues that sensors typically add. A sensorless motor control approach generally involves at least two main operations: 1) roughly estimating the motor position (e.g., where the rotor angle is) and 2) rotationally smoothing the rough estimates (e.g., by using a rotational smoother). A rotational smoother is generally defined as a lowpass filter applied to a value the modulus domain, viz. an angle that proceeds from 0 to 360 degrees, and then starts again at 0 degrees.
FIG. 1 shows a conventional sensoriess, field-oriented control (FOC) motor control system 100 in accordance with the prior art. Motor control system 100 generally includes a motor controller 102, a power supply 112, an inverter 114, and a motor 116. The motor 116 is typically a permanent magnet synchronous motor (PMSM) or brushless direct current (BLDC) motor. The motor controller 102 generally comprises a field-oriented control (FOC) algorithm block 104, an inverse Clarke converter 105, a pulse width modulation (PWM) controller block 106, and an observer 108. The inverse Clarke converter 105 performs inverse Clarke transformations on the outputs from FOC algorithm block 104. The motor controller 102 further includes a Clarke converter 109 for respectively receiving three signals from motor 116 and performing Clarke transformations thereon. The Clarke converter 109 converts the three input signals from motor 116 to two output signals. The two output signals from the Clarke converter 109 are fed into a Park converter 110 for performing Park transformations which are complex rotations.
During operation, the PWM controller block 106 of motor controller 102 provides continuous PWM signals to control inverter 114 so that inverter 114 can provide commanded voltage to each phase of motor 116 from power supply 112. Motor controller 102 provides control of motor 116 through the application of PWM signals from PWM controller block 106 based on the FOC algorithm in FOC algorithm block 104. Observer 108 determines the rotor position or angle and provides an angle signal to the Park converter 110 and PWM controller 106.
However, problems do exist with the use of conventional, sensorless FOC motor controls. For example, system 100 is complex and typically requires simultaneous current and/or voltage measurements. Because of these required simultaneous current and/or voltage measurements, observer 108 is therefore required to perform intensive computational processes and algorithms involving complex mathematics and calculations. Thus, observer 108 is typically limited from a computational process standpoint. Also, a conventional system may employ multiple observers, and these multiple observers will compete with each other in ways that can ultimately impact system performance. Furthermore, another major problem with observer 108 is that there exists a lot of noise sensitivity due to sampling in the conventional system and thus accuracy and clarity of what is observed by observer 108 is impacted. Observer 108 also requires the use and sensing of both motor voltage V and motor current I and thus the observation process of what observer 108 is trying determine from the motor voltages and currents may not be that straight forward.
An exemplary, prior art conventional motor control system that uses an observer is disclosed in U.S. Patent Application Publication No. US2012/0249033 to inventor Ling Qin entitled “Sensorless Motor Control” (hereafter referred to as '033 Patent Application). Paragraph 0005 of the '033 Patent Application further cites exemplary conventional motor control systems with observers in accordance with the prior art.
With respect to sensorless motor control systems, another way of handling the estimating and smoothing of the estimations of the rotor position is by using a sliding mode observer. The sliding mode observer both performs the estimation and smooths the estimated positional values. The Texas Instruments' (TI) white paper entitled “Designing High-Performance and Power-Efficient Motor Control Systems” by Brett Novak and Bilal Akin dated June 2009 provides an example of such a sliding mode observer (e.g., referred to as SMOPOS in the TI white paper). Yet another way of handling the estimating and smoothing operations is using a position estimator to do the position estimates and then use a phase-locked loop (“PLL”) to do the smoothing of the positional estimated values.